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What are the structural characteristics of written scientific explanations that make them good? This is often difficult to measure. One approach to describing and analyzing structures is to employ network theory. With this research, we aim to describe the elementary structure of written explanations, their qualities, and the differences between tho...
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... explanations were written and analyzed in German. The context of the explanation is the phenomenon of apparent depth (see Figure 2). This everyday phenomenon makes objects appear closer to the water surface than they are when observed from outside of the water. ...
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... the other hand, the student map is made up of small vertices that do not vary in size much. This is confirmed by Figure 12, in which boxplots for the betweenness centrality of all vertices are shown for all our student and expert maps. What is clearly seen is that all expert maps have positive outliers, whereas there are only a few and less extreme outliers for the student maps. ...
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What are the structural characteristics of written scientific explanations that make them good? This is often difficult to measure. One approach to describing and analyzing structures is to employ network theory. With this research, we aim to describe the elementary structure of written explanations, their qualities, and the differences between tho...
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... The approach presented in the manual aims to fill this gap by describing how to extract and visualize the propositional and elementary structure of written explanations using networks (so-called Element Maps). A brief description of the method has appeared in the context of studies that analyzed data using this approach (Wagner & Priemer, 2023;Wagner et al., 2020). Yet, it lacked a methodological foundation, a detailed guide, and the original development for German-language explanations does not transfer to English-language texts without adjustments, and vice versa. ...
... Propositions themselves consist of interconnected elements (entities and relations), which I refer to as the elementary structure. This elementary structure can be represented as a network, which I call the Element Map and is particularly relevant for explanations (see e.g., Wagner & Priemer, 2023;Wagner et al., 2020). ...
... In this map, three out of the 108 elements stand out in terms of centrality, with one among these three being particularly prominent in terms of centrality. These characteristics align with previous findings that identify high complexity, coherence, appropriateness, and the presence of a few central elements around which the explanation is structured, as hallmarks of expert explanations (Wagner & Priemer, 2023;Wagner et al., 2020). Figure 7, this map is smaller and exhibits less complexity, characterized by a more chain-like structure. ...
This paper introduces a novel analytical framework for dissecting and visualizing the fine-grained structure of scientific explanations through Element Maps. It delves into the methodological principles that transition from grammatical surface structures to deeper sense-making layers, such as propositions and individual elements. The manual outlines a two-part process designed to deconstruct written text into evaluable propositions which can then be refined into a granular elementary structure. This approach is illustrated through the analysis of an explanation for the day-night cycle, demonstrating the utility of Element Maps in capturing features like the complexity, coherence, and appropriateness of explanations as well as use of key terms. By representing the elementary structure in a network visualization, the study highlights how Element Maps can serve as a useful tool for educators and researchers in understanding the structure of an explanation which can be used to help learners write better scientific explanations. Beyond the analysis of explanations, the application of this method on scientific arguments is discussed. Examples and a glossary of grammatical terms support support science educators in using the presented approach.
... For example, Bruun et al. (2019) applied semantic networks to analyse annotated speech as text to characterise the whole content of the discussion. This approach adopts the same techniques used in the network analysis of textbooks (Yun & Park, 2018) and students' written answers (Wagner et al., 2020). Similar, but distinct from semantic networks, are conceptual networks that study subject-specific concepts found in texts or utterances (Caballero et al. 2020) or in concepts maps (Koponen & Nousiainen, 2019). ...
Lately, new materialism has been proposed as a theoretical framework to better understand material-dialogic relationships in learning, and concurrently network analysis has emerged as a method in science education research. This paper explores how to include materiality in network analysis and reports the development of a method to construct network data from video. The approaches, 1) information flow, 2) material semantic and 3) material engagement, were identified based on the literature on network analysis and new materialism in science education. The method was applied and further improved with a video segment from an upper secondary school physics lesson. The example networks from the video segment show that network analysis is a potential research method within the materialist framework and that the method allows studies into the material and dialogic relationships that emerge when students are engaged in investigations in school.
... Various tools were developed to make these difficulties visible, interviews (Yeo & Gilbert, 2014) and paper-and-pencil studies (Zarkadis & Papageorgiou, 2020) with learners were conducted, and their drawings were analyzed (De Andrade, Freire, & Baptista, 2021;McLure, Won, & Treagust, 2021;Park, Chang, Tang, Treagust, & Won, 2020). There are also various mapping methods for visualizing the conceptual structure of an explanation (Siew, 2020;Wagner, Kok, & Priemer, 2020). So far, however, the essential seam between phenomenon and theory in the conceptual structure of explanations remains widely unexplored. ...
... The procedure for adapting concept maps to the elementary structure of written explanations were introduced by Wagner et al. (2020). In summary, the modifications consist of four steps. ...
Scientific explanations pose significant challenges to scientists and learners. In explanations, phenomena and theories are linked, which is often a major problem for learners. Therefore, precise exploration of this gap between phenomenon and theory in written explanations is particularly relevant. However, so far it has not yet been well visualized. Concept maps offer a suitable possibility for visualization here but still need to be adapted to the structure of written explanations, especially for focusing on the gap. This paper explores the difficulties of physics learners in 56 explanations of refraction phenomena at the gap between phenomenon and theory. Therefore, concept maps have been modified. The study demonstrates that and why linking phenomenon and theory is particularly difficult. With the help of the results, fruitful conclusions for science learning can be drawn.
This study aims to find out the use of cohesive grammatical devices in twelfth-grade students’ explanation texts. In addition, this study also aims to explore the types of grammatical cohesion specifications in their essays. In this study, the researcher wanted to find out how good the quality of their student’s writing explanation texts was. To achieve this goal, the researcher used the conceptual framework of Halliday and Hasan (1976) regarding grammatical cohesion. This study applied to the twelfth grade of the Senior High School Level. The research uses descriptive and analytic studies by assigning students to write the texts. The result from the students’ explanation texts as the data in this research, there are 146 cohesive grammatical items found in students’ explanation texts. The reference occurs 68 times which has 46.5 of percentages. Conjunction occurs 53 times with 36.3% percent. Substitution occurs 23 with 15.7% percent. Ellipsis occurs two times with the lowest rate of 1.3%. The result shows that all four types of grammatical cohesion appear in students’ explanatory texts, which are the primary data in this study. However, there are subtypes of cohesive devices that don’t exist in students’ explanation texts from all of those devices. The most dominant was the reference and conjunction; on the other hand, ellipsis was the smallest presentation among grammatical cohesive, and only a few students used them. The result also indicated that the lack of grammatical cohesion devices used in terms of the generical structure of explanation text, knowledge, and ability in writing leads the college students to use inappropriate grammatical cohesion devices to be applied to this type of text. Thus, this study comes up with feedback to teachers that the discussion on the structural writing of texts and the use of coherence and cohesion should be more intensive.
Instructional strategies employing complex problem-solving examine how learners represent the problem space and argue for decisions. Unlike problems with few solutions (e.g., multiple choices), instructors struggle to evaluate solutions to ill-structured problems quickly and consistently across students. This prevents instructors to provide timely feedback to learners, who may continue to engage in erroneous thinking. Despite the availability of several software packages to assess the learners’ works as maps, several barriers still prevent the wide-scale adoption of such assessment systems by instructors. We examine three open questions and identify opportunities from Artificial Intelligence to develop the next generation of assessment systems.
